Data Technology Trend #7: Monetized

Trend 7.1: Data & AI Market Places and exchanges platforms

Data can be best monetized if the organization can build Data & AI marketplace and exchange platforms are it for internal or external use.

Data Market Place by Snowflake:

  • Discover the Data that Drives Insight
  • Reduce Data Integration Costs
  • Access Fresh Data Faster

Other notable Market places:

Sample Reference architecture to publish your data to Market Place (AWS):

Sample Reference Architecture

AWS Data Exchange (Link):

AWS Data Exchange is building as a central market place where you can find and subscribe to data. Quality and refined data from qualified data providers are included as per AWS. Providers such as Healthcare, Finance, etc. participate in this market place.

  • Quickly find diverse data in one place
  • Efficiently access data in the cloud
  • Easily analyze new data

Trend 7.2: Data As A Service

Data-as-a-service (DaaS) is a data management strategy and/or deployment model that focuses on the cloud (public or private) to deliver a variety of data-related services such as storage, processing, and analytics.

Databricks:

Data Bricks Delta Share and Unity Catalog released in 2021 are excellent candidates for Data As A service.

Trend 7.3: Data As A Product

Data-As-A-Product Model:

  • Data flow is unidirectional
  • Data has SLA
  • Data will have problems and anomalies, stakeholder’s understanding is the key hence product-driven must be combined with stakeholder-driven development.
  • Any product that is mentioned in Data Market Place, if you publish to the market place, then it becomes “Data As A Product”.

--

--

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
LAKSHMI VENKATESH

LAKSHMI VENKATESH

625 Followers

All the views expressed here are my own views and does not represent views of my firm that I work for. Data | Big Data | Cloud | ML